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        "description": "=============\nData-Xray\n=============\n\nData-Xray provides a Pythonic interface to organization and analysis of\ndata, acquired primarily with Nanonis controllers, manufactured by Specs GmbH.\n\nThe primary emphasis at the moment is on scanning probe microscopy measurements,\nbut most of the analysis applies to other domains of hyperspectral data.\n\nData organization is achieved through the use of xarray structure - which is \nan ingenious extension of Pandas phenomenology onto arbitrary dimensions.\n\nData-Xray draws upon many truly excellent python libraries, for which we as developers\nare phenomenally greatful. \n\nInstallation / Setup\n********************\n\nUse pip to install the library:\n\n    pip install data-xray\n\n\n**Testing**\n\nThere are a few ways to run the unit tests.\n\nOne option is to use the shell script in the root of the repository\ncalled *test.example.sh*. Copy it using ``cp test.example.sh test.sh``.\nEdit *test.sh* to include your Cicero API username and password. Then, run\nthe tests using ``./test.sh``.\n\nAnother option is to edit the ``test/tests.py`` file directly, adding your\nCicero API credentials where indicated. Doing so will allow you to execute\ntests using ``nosetests`` (if you have the nose package installed), or\nusing ``python setup.py test``, or invoking the ``tests.py`` file itself.\n\nDocumentation\n*************\n\n\n\nHelp!\n*****\n\nLicense\n*******\n\ndata-xray is licensed under the Apache 2.0 license. See ``LICENSE.txt`` for\nmore details.\n\nContribute\n**********\n\nSee a bug? Want to improve the docs or provide more examples? Thank you!\nPlease open a pull-request with your improvements and we'll work to respond\nto it in a timely manner.\n\n\n",
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        "license": "LICENSE.txt",
        "maintainer": "Petro Maksymovych",
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